Reconfigurable Polarization Converter Using Liquid Metal Based Metasurface
Bibliographic record
Abstract
A multifunctional reconfigurable metasurface based on liquid metal injection is presented. The reflective flexible material metasurface formed by two switchable microfluidic layers— the top layer comprising an array of meandered half-rings and the lower layer, straight meander lines—can be reconfigured into four states. The proposed metasurface becomes a reflector with emptied channels, whereas it exhibits linear-to-circular polarization conversion (or linear-to-cross-polarization conversion) properties when the top (or bottom) layer is filled with a liquid metal alloy. Upon normal excitation of linearly u/v-polarized waves and activation of the bottom layer, the metasurface reflects cross v/u-polarized waves in the frequencies from 9.83 to 17.42 GHz (53% bandwidth) with a polarization conversion ratio (PCR) of at least 90%. On the other hand, the metasurface operates as a linear-to-circular polarizer (for u/v-polarized waves) over 8.97–11.30 GHz (23% bandwidth), reflecting left- or right-hand circularly polarized waves. To verify the polarization conversion performance, a$25\times 25$element metasurface array is fabricated and measured. The experimental results confirm the simulation results over the 8–12 GHz test band. The compactness, structural flexibility, and multifunctionality of the proposed metasurface make it a suitable candidate for modern integrated antenna array systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".